This R Notebook and its related R scripts provide an introduction to the COVIDMINDER application, which you can find at:
The github repository for all the code required for this notebook, including a snapshot of the COVIDMINDER application, can be found at:
The COVIDMINDER github repository can be found at:
We’re asking those who wish to participate in this excercise to clone the github repository, create a personal branch, and make additions to the repository by creating new, customized notebooks. The general procedure is as follows:
git clone https://github.com/TheRensselaerIDEA/COVID-Notebooks.git in your home directory, creating a new directory COVID-Notebookscd to COVID-Notebooksgit checkout -b feature-id where id is the github issue number your branch will address
Issue #99, your new branch should be feature-99feature-99-1COVID-Notebooks via the Files panelRmd) file using an original, descriptive filenamedata/csv subdirectory.git add each file you want to add to the repository (e.g. your new Rmd file, perhaps the html you create when you knit)git commit -a -m "some comment" where “some comment” is a useful comment describing your changesgit push origin feature-id (where feature-id is the branch you’re working on)Please also see this handy github “cheatsheet”: https://education.github.com/git-cheat-sheet-education.pdf
data/ directory hierarchy, mostly under data/csv/ and data/csv/time_series/data/csvdata/csv/time_series/
The advantage of the disparity index is that represents how far off a target standard the observed rate is.
Mathematically, DI = log(x/y) or DI = log(y/x) depending upon whether being above or below the target is preferred.
This map compares the COVID-19 mortality rates of individual states with the US rate. This map is updated daily.
Here, shades of red indicate that a state’s COVID-19 mortality rate is higher than the US rate
Data source: JHU daily reports (04-07-2020)
This map compares rates of COVID-19 tssting in US states vs South Korea’s testing rate. This map is updated daily.
Here, shades of red indicate that a state’s testing rate is lower than the South Korean rate
Data source: The COVID Tracking Project daily reports (04-07-2020)
The map compares individual state mortality rates related to cardiovascular diseases (per 100k) with the US rate. In recent literature, COVID-19 risk has been linked to certain cardiovascular diseases, including hypertension. This map uses recent historical figures.
Here, shades of red indicate that a state’s mortality rate from total cardiovascular diseases is higher than the US rate
Data source:
CDC (2017)
This map compares the availability of hospital beds in US states vs the rate in Italy (3.2 beds/1000). This map uses recent historical figures and does not reflect ‘surge’ capacity.
Here, shades of red indicate that a state’s hospital bed availablity is lower than the rate in Italy
Data sources:
Organisation for Economic Co-operation and Development and Kaiser Family Foundation
This map compares the COVID-19 mortality rates of NY counties with the NY average. This map is updated daily.
Here, shades of red indicate that a county’s COVID-19 mortality rate is higher than the NY rate.
Data source: JHU daily reports (04-06-2020)
This map compares the COVID-19 cases for NY counties with the NY average. This map is updated daily.
Here, shades of red indicate that a county’s COVID-19 case count is higher than the NY rate.
Data source: JHU daily reports (04-06-2020)
This plot shows the growth of COVID-19 cases across NY counties since early 2020. This data is updated daily.
Mouse over the plot to identify individual counties.
Data source: JHU daily reports (04-06-2020)